CVE-2025-23353: Nvidia Megatron-lm RCE Vulnerability

CVE-2025-23353 Overview

CVE-2025-23353 is a code injection vulnerability in NVIDIA Megatron-LM affecting all platforms. The flaw resides in the msdp preprocessing script, which improperly handles attacker-supplied data. An authenticated local user can craft malicious input to trigger code injection during preprocessing operations.

Successful exploitation may lead to arbitrary code execution, privilege escalation, information disclosure, and data tampering. The issue is tracked under CWE-94 (Improper Control of Generation of Code).

Critical Impact
Local attackers with low privileges can execute arbitrary code within the Megatron-LM training environment, compromising confidentiality, integrity, and availability of AI model training pipelines.

Affected Products

NVIDIA Megatron-LM (all versions prior to the fixed release)
NVIDIA Megatron-LM 0.13.0 release candidates (rc0 through rc4)
NVIDIA Megatron-LM 0.13.0 general availability build

Discovery Timeline

2025-09-24 - CVE-2025-23353 published to NVD
2026-06-17 - Last updated in NVD database

Technical Details for CVE-2025-23353

Vulnerability Analysis

The vulnerability exists in the Multi-Stage Dialogue Prompting (msdp) preprocessing script bundled with NVIDIA Megatron-LM. The script processes user-supplied dataset content but fails to properly validate or sanitize that input before passing it into code-generation or evaluation paths. An attacker who can place malicious content into the preprocessing input can influence code execution.

Because Megatron-LM is used to train large language models on high-value GPU infrastructure, exploitation can pivot from a benign-looking dataset artifact to full compromise of the training host. The attack requires local access with low privileges and no user interaction.

Root Cause

The root cause is improper control of generated code within the msdp preprocessing routine. The script constructs or evaluates code paths from untrusted data without adequate sanitization, matching the CWE-94 pattern. Any dataset field the attacker controls becomes an injection sink.

Attack Vector

An attacker with local access supplies crafted dataset files or preprocessing arguments to the Megatron-LM training pipeline. When the msdp script processes these inputs, the injected payload is interpreted as code. The resulting execution runs with the privileges of the training job, which is typically a service or research account with access to model weights, datasets, and GPU resources.

No public proof-of-concept exploit has been released. The vulnerability has not been observed under active exploitation and is not listed in the CISA Known Exploited Vulnerabilities catalog.

See the NVIDIA Support Article for vendor-supplied technical details.

Detection Methods for CVE-2025-23353

Indicators of Compromise

Unexpected child processes spawned by Python interpreters running Megatron-LM preprocessing scripts
Anomalous file writes, outbound network connections, or shell invocations originating from msdp preprocessing jobs
Modification of training datasets or preprocessing configuration files by non-administrative users

Detection Strategies

Inspect preprocessing input files for embedded Python expressions, format-string payloads, or shell metacharacters targeting the msdp pipeline
Monitor training hosts for process lineage where python invoking msdp spawns interactive shells, package installers, or reverse-connection tooling
Baseline normal Megatron-LM job behavior and alert on deviations in system calls, file access patterns, and network egress

Monitoring Recommendations

Enable audit logging on directories containing Megatron-LM datasets and preprocessing scripts
Correlate GPU workload telemetry with endpoint process events to identify training jobs performing non-training activity
Ship host telemetry from ML infrastructure into a centralized analytics platform for retroactive hunting against the injection pattern

How to Mitigate CVE-2025-23353

Immediate Actions Required

Upgrade NVIDIA Megatron-LM to the fixed version identified in the NVIDIA Support Article
Restrict local access to Megatron-LM training hosts to trusted operators and service accounts
Audit existing datasets and preprocessing inputs for suspicious content that may have been staged prior to patching

Patch Information

NVIDIA has published guidance and updated builds through security bulletin answer ID 5698. Administrators should apply the vendor-supplied update to all Megatron-LM installations, including 0.13.0 and its release candidates. Additional record details are available in the NVD entry for CVE-2025-23353 and the CVE.org record.

Workarounds

Run Megatron-LM preprocessing inside isolated containers or sandboxes with minimal filesystem and network privileges
Enforce strict least-privilege on the user account executing msdp preprocessing and remove write access to shared model artifacts
Validate and sign dataset inputs before they enter the preprocessing pipeline to prevent tampered content from reaching the vulnerable script

bash

# Configuration example: pin Megatron-LM to the patched release and constrain runtime
pip install --upgrade nvidia-megatron-lm

# Execute preprocessing in a restricted container
docker run --rm \
  --read-only \
  --network=none \
  --user 10001:10001 \
  -v /data/datasets:/data:ro \
  megatron-lm:patched \
  python tools/msdp/preprocess.py --input /data/clean.jsonl